Last updated: 17th December 2025
1. Postdoctoral Research Assistant in AI Scientists
We are seeking a full-time Postdoctoral Research Assistant to join Torr Vision Group at the Department of Engineering Science, central Oxford. The post is funded by EPSRC and is fixed-term to the 30th September 2026.
We are looking for outstanding machine learning researcher to join the Torr Vision Group and work on AI Scientists: systems that use foundation models, AI agents, and robotics to automate scientific discovery in both the natural and social sciences.
The postholder will contribute to one or more of the following strands:
• Foundational work on large-scale/foundation models and agentic architectures for autonomous scientific reasoning and planning;
• AI social scientists, including language-model-based and agent-based simulations for social science domains such as history, economics, and other areas of computational social science;
• AI scientists for natural science, integrating LLM agents with simulation and, where appropriate, robotic experimentation (e.g., automated “dry” and “wet” lab workflows).
You will be able to Design, develop and implement algorithms and systems based on foundation models, large language models and/or AI agents for automated scientific discovery, in natural science and/or social science domains.
Candidates should possess a PhD (or be near completion) in PhD in Computer Science, AI, Security, or a related field. You will have a Strong background in machine learning and/or computer security and Experience working with LLMs or agent-based systems.
Informal enquiries may be addressed to Professor Philip Torr.
For more information about working at the Department, see working at the Department.
Only online applications received before midday on 7th January 2026 can be considered. You will be required to upload a covering letter/supporting statement, including a brief statement of research interests (describing how past experience and future plans fit with the advertised position), CV and the details of two referees as part of your online application.
The Department holds an Athena Swan Bronze award, highlighting its commitment to promoting women in Science, Engineering and Technology.
2 Postdoctoral Research Assistant in Machine Learning
We are seeking a full-time postdoctoral researcher to join Torr Vision Group at the Department of Engineering Science (central Oxford). The post is funded by EPSRC and is fixed-term for one year with the possibility of renewal.
This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly in continual learning settings. The core focus is on leveraging Reinforcement Learning (RL) to make the training and deployment of LLMs more computationally and sample efficient. This approach aims to improve the accessibility, scalability, and sustainability of LLMs. The research will span foundational advances in RL/LLM integration to applied work with potential real-world impact. You will conduct cutting-edge research at the intersection of RL and LLMs. You will also design and run experiments to improve LLM efficiency and sustainability.
You will hold a relevant PhD/DPhil or be near completion* together with relevant experience. You will have a strong technical background in machine learning, especially RL and LLMs. An ability to work independently and as part of a collaborative research team is essential.
Informal enquiries may be addressed to Dr. Yangchen Pan: email
For more information about working at the Department, see working at the Department.
Only online applications received before midday on 5th January, 2026 can be considered. You will be required to upload supporting statements, including a brief statement of research interests (describing how past experience and future plans fit with the advertised position, two pages recommended), CV and the details of two referees as part of your online application.
The Department holds an Athena Swan Bronze award, highlighting its commitment to promoting women in Science, Engineering and Technology.
Apply here
3. Fourth Year Project/Master Thesis
If you are a student at Oxford, have a specific research direction in mind, and aspire to publish in top conferences, please reach out to Professor Torr. philip.torr@eng.ox.ac.uk